Nvidia takes its GPU to the enterprise cloud

Summary:The graphics chip specialist has shown off Tesla chips and other technology based on its new Kepler GPU architecture, which it says can boost desktop virtualisation, BYOD and 'democratise' supercomputing

On Tuesday, the graphics chip specialist unveiled two new Tesla GPUs, the K10 and K20, and its Nvidia VGX platform for virtualised desktops. It also showed off a preview of its Cuda 5 parallel programming platform.

Cuda and Kepler-based products will continue to put GPU-accelerated computing into more hands, according to the company's chief executive Jen-Hsun Huang.

"The democratisation of high-performance computing is happening right in front of us," Huang told an audience at Nvidia's GPU Technology Conference in San Jose, on Tuesday.

Parallel computing

With roughly three times the performance at the same power as the
earlier Fermi processors, Kepler introduces two key features that
improve its parallel computing performance.

Dynamic parallelism adds
support for run-time dependencies in Cuda applications. This means that work can
be created on the GPU, rather than passing from CPU to GPU each time
new threads are needed. In doing this, it simplifies the algorithms needed for
data-dependent applications, making them more efficient — for example,
allowing finite-element analysis applications to use adaptive meshes.

"Kepler is a very big deal for Nvidia," Huang said. "Graphics to the next level and GPU in the cloud."

Kepler processors

Nvidia's new Tesla products are "computing accelerators built to handle the most complex HPC problems in the world", according to the company. Both are based on the same Kepler technology found in the GeForce GTX 690 graphics card, part of the Nvidia's GPU line for consumer devices.

The Kepler processors have 192 cores and,
initially, 3.8 billion transistors. In its second generation, the K20 will have over seven billion transistors, making it the
most complex processor in the market, according to the manufacturer.

Kepler is a very big deal for Nvidia. Graphics to the next level and GPU in the cloud.

– Jen-Hsun Huang, Nvidia

Tesla K10 will offer single-precision floating point performance of 4.58 teraflops and 320GB per second bandwidth, and it is intended for imaging, signal processing and
seismic processing applications. Available in May, it will be followed towards
the end of 2012 by the K20, the flagship model in the Tesla family.

The Tesla K20 has been built for intensive high-computing. It is tuned for double-precision
operations. It also has support for dynamic parallelism and Hyper-Q.

Some of the new capabilities include real-time ray-tracing support and an improved physics engine. While these are "a big deal for graphics, they're a bigger deal for high-performance computing", Huang said.

Virtual GPU

On stage, Huang also introduced the Nvidia VGX platform, which is targeted at BYOD scenarios in enterprises. The support for GPU virtualisation means that businesses can get "the largest and most powerful GPU, that's also the smallest and most power efficient; one we can all share", Huang said.

The virtual GPU capabilities in Kepler will improve remote workers' experience with virtual desktops, he said, noting that the platform allows several desktops to share the same GPU.

"Employees can now access a true cloud PC from any device — thin client,
laptop, tablet or smartphone — regardless of its operating system, and
enjoy a responsive experience for the full spectrum of applications
previously only available on an office PC," Nvidia said in a statement.

Nvidia is partnering with server manufacturers including HP, Dell and IBM, as well as with VDI providers to add GPU virtualisation support to Citrix XenDesk, VMWare's VDI tools, and Microsoft's Hyper-V and RemoteFX. Nvidia demonstrated various use cases, delivering complete Windows desktops with workstation applications to tablet PCs and lightweight notebooks.

Beyond business computing, Nvidia unveiled a cloud game-streaming platform at the conference. The GeForce Grid uses Kepler virtualised GPUs to deliver games over a network with low latency.

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Born on the Channel Island of Jersey, Simon moved to the UK to attend the University of Bath where he studied electrical and electronic engineering. Since then a varied career has included being part of the team building the world's first solid state 30KW HF radio transmitter, writing electromagnetic modelling software for railguns, and t...
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